Latest Videos
Science seminars, challenge webinars, and workshop recordings from the OpenADMET community.
Hugo MacDermott-Opeskin, OpenADMET: A Machine Learning First Approach to ADMET and Drug Discovery
A seminar from our very own Hugo MacDermott-Opeskin sponsored by MedChem Australia at WEHI Melbourne.
Watch →Brian Wylie, SuperCowPowers — ML Factories: Create, Deploy, and Manage 1,000 ADMET Models,
Brian from SuperCowPowers discusses engineering challenges and strategies that he uses to makes large-scale ADMET ML on AWS practical.
Watch →Chris Taylor, QCWare — Lessons from tackling the OpenADMET challenges with Promethium
Chris and the folks at QCWare share their use of the Promethium platform for QM and DFT derived approaches in the recent OpenADMET challenges
Watch →Matt Robinson, PostEra — Confusion Without Measure
Matt Robinson from PostEra presents on his paper exploring unit confusion in ADMET: Confusion Without Measure: Units, Assumptions, and Best Practices in Reporting Preclinical ADME/PK Data.
Watch →Predicting PXR Induction — Learnings From Top Performers in Our Blind Challenge
Duncan Muir (Inductive Bio), Yanjun Li (University of Florida) and Asa Barth-Maron (Antares Therapeutics) detail the computational pipelines behind their top Activity Track submissions, their modeling strategies for PXR…
Watch →Lessons in PXR structure from the OpenADMET PXR blind challenge
Join us for this webinar featuring the winners of the structure track of our PXR blind challenge
Watch →Karim Ben Hicham, RWTH Aachen — Tabular foundation models for molecular properties
Karim Ben Hicham shares his work on using tabular foundation models (TFMs) for in-context prediction of molecular properties. He covers why TFMs work and demonstrates some impressive results.
Watch →Community Insights on the OpenADMET PXR challenge
Join us for this webinar featuring two outstanding participants from the OpenADMET PXR Blind Challenge who shared their results and engaged the community!
Watch →David Araripe, University of Leiden — Curating data from ChEMBL with Capricho
David Araripe shares his work on Capricho, a package for curating data efficiently from ChEMBL, as well as exploring downstream effects on QSAR model performance.
Watch →Leveraging Public Data in the OpenADMET ExpansionRx Blind Challenge
Join us for this webinar with two teams from our recent OpenADMET ExpansionRx Blind Challenge. Team shin-chan led by Bart Lenselink and Davide Araripe from StructureTx and University of Groningen respectively, were top…
Watch →Andrew Ligeralde, PhareBio — QSAR Modeling for Property Prediction and Generative Design
Andrew Ligeralde from Phare Bio presents on the modelling and generative design strategies used at Phare Bio to develop the next generation of antibiotics.
Watch →Srijit Seal, University of Cambridge — Making Machine Learning Successful in Drug Discovery
Srijit Seal presents on the pillars of making machine learning successful in drug discovery, as well as some recent results from blind challenges run by OpenADMET.
Watch →Applying a Focused Modeling Strategy in the OpenADMET ExpansionRx Blind Challenge
Join us for this CDD webinar with Alex Rich from Inductive Bio and Daniel Crusius from deepmirror, top performers in the OpenADMET ExpansionRx Blind Challenge. Alex and Daniel will describe the modeling approaches their…
Watch →Applying Real-World Drug Discovery Experience in the OpenADMET ExpansionRx Blind Challenge
Join us for this webinar with CDD, where Jason Wang from Merck & Co and Davide Boldini from EMD Serono/Merck KGaA, from the recent OpenADMET ExpansionRx Blind Challenge, describe how they drew on years of experience in…
Watch →Ruel Cedeno, Novalix — OpenADMET Science Seminar
Ruel Cedeno of Novalix presents an OpenADMET Science Seminar on lessons learned on in silico ADME predictions from participating in blind challenges.
Watch →Jackson Burns, MIT — OpenADMET Science Seminar
Jackson Burns of the Green Lab at MIT presents on the CheMeleon foundation model for molecular property prediction, and how it applies to ADMET modeling.
Watch →ASAP x PolarisHub x OpenADMET Workshop
A joint hands-on workshop from ASAP, Polaris Hub, and OpenADMET, walking through open tools and benchmarks for building and evaluating predictive ADMET models. Recorded April 30, 2025.
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